Project Summary/Abstract Sleep is vital for optimal cognitive function. Yet, we do not understand how it influences and regulates neuronal assemblies in the brain. Studies over the past several decades have presented compelling evidence that rest is correlated with subsequent improved cognitive performance. For instance, people who rest or take a nap after performing a new task remember it better and exhibit an elevated performance compared to those who do not rest. Despite the prevalence and impact of sleep on behavioral performance, little is known about the neural mechanisms of this improvement. Specifically, what is the impact of rest on sensory coding by individual neurons and networks, and how does post-rest neuronal coding accuracy influence behavioral performance? We will address this issue by examining whether brief sleep (20 min of rest) influences visual perceptual performance and the coding of information across visual cortical layers. To accomplish this goal, we will use multiple-electrode recording of single-unit activity and local field potentials (LFPs) in macaque mid-level visual cortex (area V4) while the animals will perform a discrimination task before and after rest. Aim 1 will examine whether rest improves stimulus coding in single neurons of each V4 cortical layer. Measures related to coding, sensitivity of single neurons and the degree of synchrony between neuronal responses and LFPs, will be examined. Aim 2 will examine whether rest improves network coding in a layer-specific manner by measuring whether rest (i) decreases correlated activity across the network, (ii) diminishes the level of synchrony in the population response, and (iii) increases the amount of information in population activity. Aim 3 will examine whether rest improves behavioral performance and whether rest influences the relationship between layer-dependent neuronal coding and behavioral performance by examining (i) whether behavioral performance is improved after rest, (ii) whether the post-rest network performance is correlated with behavioral performance, (iii) whether synchronous population activity during rest is correlated with desynchronized post-rest population activity and with improved behavioral performance, and (iv) whether there is a relationship between the amount of rest and the improvement in network and behavioral performance. Overall, this proposal will expand our understanding of the neurobiology of sleep and of the neuronal coding driving perception and thus, provide future solutions to ameliorate sleep disorder and its detrimental effects on cognitive performance.